Comparison of phase structures and surface free energy values for the coatings synthesised from linear polyurethanes and from waterborne polyurethane cationomers

WAXS, DSC and AFM methods were employed to compare phase structures of the coatings obtained from waterborne polyurethane cationomers which had been synthesised in the reaction of some diisocyanates (MDI, IPDI, TDI and HDI) with polyoxyethylene glycols (M = 600 and 2,000) and butane1,4-diol or N-methyl- or N-butyldiethanolamine and 2,2,3,3-tetrafluoro-1,4-butanediol. The structures were also analysed of the coatings derived from linear polyurethanes which had been synthesised on the basis of similar raw materials. Better rigidity was found for generally amorphous cationomer coats. Changes were discussed in the surface free energy (SFE) values and in their components, as calculated independently with the use of the van Oss–Good and Owens–Wendt methods. Polyurethane coats turned out more hydrophobic as compared to cationomer ones. In both coat types, fluorine incorporated into cationomers contributed to lower SFE values: from 50 down to about 30 mJ/m2

In Silico Insights into the Symbiotic Nitrogen Fixation in Sinorhizobium meliloti via Metabolic Reconstruction

BACKGROUND: Sinorhizobium meliloti is a soil bacterium, known for its capability to establish symbiotic nitrogen fixation (SNF) with leguminous plants such as alfalfa. S. meliloti 1021 is the most extensively studied strain to understand the mechanism of SNF and further to study the legume-microbe interaction. In order to provide insight into the metabolic characteristics underlying the SNF mechanism of S. meliloti 1021, there is an increasing demand to reconstruct a metabolic network for the stage of SNF in S. meliloti 1021. RESULTS: Through an iterative reconstruction process, a metabolic network during the stage of SNF in S. meliloti 1021 was presented, named as iHZ565, which accounts for 565 genes, 503 internal reactions, and 522 metabolites. Subjected to a novelly defined objective function, the in silico predicted flux distribution was highly consistent with the in vivo evidences reported previously, which proves the robustness of the model. Based on the model, refinement of genome annotation of S. meliloti 1021 was performed and 15 genes were re-annotated properly. There were 19.8% (112) of the 565 metabolic genes included in iHZ565 predicted to be essential for efficient SNF in bacteroids under the in silico microaerobic and nutrient sharing condition. CONCLUSIONS: As the first metabolic network during the stage of SNF in S. meliloti 1021, the manually curated model iHZ565 provides an overview of the major metabolic properties of the SNF bioprocess in S. meliloti 1021. The predicted SNF-required essential genes will facilitate understanding of the key functions in SNF and help identify key genes and design experiments for further validation. The model iHZ565 can be used as a knowledge-based framework for better understanding the symbiotic relationship between rhizobia and legumes, ultimately, uncovering the mechanism of nitrogen fixation in bacteroids and providing new strategies to efficiently improve biological nitrogen fixation

The unfolded protein response in immunity and inflammation.

The unfolded protein response (UPR) is a highly conserved pathway that allows the cell to manage endoplasmic reticulum (ER) stress that is imposed by the secretory demands associated with environmental forces. In this role, the UPR has increasingly been shown to have crucial functions in immunity and inflammation. In this Review, we discuss the importance of the UPR in the development, differentiation, function and survival of immune cells in meeting the needs of an immune response. In addition, we review current insights into how the UPR is involved in complex chronic inflammatory diseases and, through its role in immune regulation, antitumour responses.This work was supported by the Netherlands Organization for Scientific Research Rubicon grant 825.13.012 (J.G.); US National Institutes of Health (NIH) grants DK044319, DK051362, DK053056 and DK088199, and the Harvard Digestive Diseases Center (HDDC) grant DK034854 (R.S.B.); National Institutes of Health grants DK042394, DK088227, DK103183 and CA128814 (R.J.K.); and European Research Council (ERC) Starting Grant 260961, ERC Consolidator Grant 648889, and the Wellcome Trust Investigator award 106260/Z/14/Z (A.K.).This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nri.2016.6